Papers Word Alignment

Bidirectional American Sign Language to English Translation

We outline a bidirectional translation system that converts sentences from American Sign Language (ASL) to English, and vice versa. To perform machine translation between ASL and English, we utilize a generative approach…

Sentence-level dialects identification in the greater China region

Identifying the different varieties of the same language is more challenging than unrelated languages identification. In this paper, we propose an approach to discriminate language varieties or dialects of Mandarin Chine…

Neural Machine Translation on Scarce-Resource Condition: A case-study on Persian-English

Neural Machine Translation (NMT) is a new approach for Machine Translation (MT), and due to its success, it has absorbed the attention of many researchers in the field. In this paper, we study NMT model on Persian-Englis…

Joint Prediction of Word Alignment with Alignment Types

Automatic Creation of a Sentence Aligned Sinhala-Tamil Parallel Corpus

A sentence aligned parallel corpus is an important prerequisite in statistical machine translation. However, manual creation of such a parallel corpus is time consuming, and requires experts fluent in both languages. Aut…

A Comparison Between Morphological Complexity Measures: Typological Data vs. Language Corpora

Language complexity is an intriguing phenomenon argued to play an important role in both language learning and processing. The need to compare languages with regard to their complexity resulted in a multitude of approach…

Pairing Wikipedia Articles Across Languages

Wikipedia has become a reference knowledge source for scores of NLP applications. One of its invaluable features lies in its multilingual nature, where articles on a same entity or concept can have from one to more than …

Combining fast\_align with Hierarchical Sub-sentential Alignment for Better Word Alignments

fast align is a simple and fast word alignment tool which is widely used in state-of-the-art machine translation systems. It yields comparable results in the end-to-end translation experiments of various language pairs. …

Improving word alignment for low resource languages using English monolingual SRL

We introduce a new statistical machine translation approach specifically geared to learning translation from low resource languages, that exploits monolingual English semantic parsing to bias inversion transduction gramm…

Neural Reordering Model Considering Phrase Translation and Word Alignment for Phrase-based Translation

This paper presents an improved lexicalized reordering model for phrase-based statistical machine translation using a deep neural network. Lexicalized reordering suffers from reordering ambiguity, data sparseness and noi…

Similar Southeast Asian Languages: Corpus-Based Case Study on Thai-Laotian and Malay-Indonesian

This paper illustrates the similarity between Thai and Laotian, and between Malay and Indonesian, based on an investigation on raw parallel data from Asian Language Treebank. The cross-lingual similarity is investigated …

Integrating empty category detection into preordering Machine Translation

We propose a method for integrating Japanese empty category detection into the preordering process of Japanese-to-English statistical machine translation. First, we apply machine-learning-based empty category detection t…

Japanese Lexical Simplification for Non-Native Speakers

This paper introduces Japanese lexical simplification. Japanese lexical simplification is the task of replacing difficult words in a given sentence to produce a new sentence with simple words without changing the origina…

Bitext Name Tagging for Cross-lingual Entity Annotation Projection

Annotation projection is a practical method to deal with the low resource problem in incident languages (IL) processing. Previous methods on annotation projection mainly relied on word alignment results without any train…

A Bayesian model for joint word alignment and part-of-speech transfer

Current methods for word alignment require considerable amounts of parallel text to deliver accurate results, a requirement which is met only for a small minority of the world{'}s approximately 7,000 languages. We show t…

Learning to Identify Sentence Parallelism in Student Essays

Parallelism is an important rhetorical device. We propose a machine learning approach for automated sentence parallelism identification in student essays. We build an essay dataset with sentence level parallelism annotat…

Reading and Thinking: Re-read LSTM Unit for Textual Entailment Recognition

Recognizing Textual Entailment (RTE) is a fundamentally important task in natural language processing that has many applications. The recently released Stanford Natural Language Inference (SNLI) corpus has made it possib…

Fast Collocation-Based Bayesian HMM Word Alignment

We present a new Bayesian HMM word alignment model for statistical machine translation. The model is a mixture of an alignment model and a language model. The alignment component is a Bayesian extension of the standard H…

Inducing Bilingual Lexica From Non-Parallel Data With Earth Mover's Distance Regularization

Being able to induce word translations from non-parallel data is often a prerequisite for cross-lingual processing in resource-scarce languages and domains. Previous endeavors typically simplify this task by imposing the…

Improving Word Alignment of Rare Words with Word Embeddings

We address the problem of inducing word alignment for language pairs by developing an unsupervised model with the capability of getting applied to other generative alignment models. We approach the task by: i)proposing a…